Polyploid HLA Typing

End-to-end pipeline for chimeric (k=4) HLA typing of allo-HSCT and solid-organ transplant samples from short-read FASTQs. The detailed aggregate keeps the legacy R1/R2/D1/D2 assembly slots, while the primary mixed-sample report lists four allele copies per gene sorted by estimated copy proportion without making recipient/donor assignment part of the final call.

• Installation & environment: INSTALL.md

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1. Files

File	Role
polyphase_v2.sh	driver — run this
hla_polyphase_assemble.py	baseline typing engine (whatshap polyphase + IMGT scoring)
reassign_gt_chimeric.py	χ-aware GT correction before phasing
estimate_chi_pooled.py	pooled-continuous χ_R estimator
report_gene_abundance.py	writes the 15-gene mixture/copy-abundance and QC report
iterative_remap_em.py	EM refinement (Salmon-style read remap)
apply_quartet_optimization.py	frozen class-I read-gated and class-II joint quartet optimization
diagnostics/rescue_gene_binned_reads.py	validation-only read-bin rescue diagnostic/prototype
apply_class2_joint_rescue.py	guarded class-II post-aggregate rescue
em_refine_gate.py	per-gene EM override gate logic
aggregate_calls.py	merges per-gene calls.tsv into one summary table
evaluate_calls.py	compares <SAMPLE>.final_calls.tsv with truth_typing.tsv at 2-field and G group resolution
exon_typing_from_haps.py	exon-level G group fallback/diagnostic for high-mask genes
prepare_extra_typing_resources.py	builds augmented references for HLA-E/F/G/H and MICA/MICB typing
build_resource_indexes.sh	rebuilds HLA resource indexes when files are missing or a custom resource set is used
gene.spechla.bed	per-gene typing region on bundled hla.ref.extend.fa
resources/spechla/	bundled SpecHLA-derived helper scripts and HLA reference files
environment.yml	conda environment spec
benchmark/	simulation, scoring, and Slurm benchmark workflows; see benchmark/README.md
diagnostics/	offline diagnostics, validation runners, and rejected alternatives kept for reference
docs/	experiment protocols and extended project documentation
tests/	focused unit and integration tests

---

2. Install

See INSTALL.md. Short version:

conda env create -f environment.yml
conda activate polyploid-hla
# HLA reference resources needed by the pipeline are bundled under# resources/spechla. Set SPECHLA=/path/to/custom/resources only# when intentionally overriding them.# Optional: repair/rebuild bundled resource indexes.
bash build_resource_indexes.sh

---

3. Quick start

From the repository root:

FQ1=/path/sample.R1.fq.gz \
FQ2=/path/sample.R2.fq.gz \
SAMPLE=mySample \
RECIPIENT_MAJOR=0 \
WORK_DIR=$PWD/run_outputs \
bash polyphase_v2.sh

WORK_DIR controls where outputs are written. If it is not set, the driver uses the parent directory of polyphase_v2.sh and writes ${WORK_DIR}/asm_v2 and ${WORK_DIR}/spechla_out.

Final result files:

column -t run_outputs/asm_v2/mySample/mySample.copy_calls.tsv
column -t run_outputs/asm_v2/mySample/mySample.final_calls.tsv
column -t run_outputs/asm_v2/mySample/mySample.gene_abundance.tsv

By default, allele-copy outputs contain the six validated classical genes, the six extended genes HLA-E/F/G/H, MICA, and MICB, plus the DRB345 linked add-on row. The abundance report separates DRB345 into HLA-DRB3, HLA-DRB4, and HLA-DRB5, producing 15 gene rows in total. The extended-gene calls and abundance rows remain exploratory until independently validated.

Primary side-agnostic copy report:

sample gene copy_id copy_rank allele allele_2field copy_fraction allele_read_count copy_read_count proportion_source legacy_slot raw_copy_fraction copy_identifiability copy_fit_error
mySample HLA-A copy1 1 A*29:02:01:02 A*29:02 0.445599 1425.14 1425.14 copy_fraction_fit D2 0.445599 underdetermined_chi_regularized 0.00000000
mySample HLA-A copy2 2 A*01:01:01:01 A*01:01 0.344401 1149.35 1100.29 copy_fraction_fit R1 0.344401 underdetermined_chi_regularized 0.00000000
...

Detailed R/D-slot aggregate:

sample gene R1_full R2_full D1_full D2_full R1_report R2_report D1_report D2_report R1_read_count R2_read_count D1_read_count D2_read_count source
mySample HLA-A A*01:01:01:01 A*23:01:01:01 A*01:01:01:01 A*29:02:01:02 A*01:01 A*23:01 A*01:01 A*29:02 1149.35 623.77 1149.35 1425.14 em_refine
...

The detailed file keeps both high-resolution calls and conservative report calls:

• *_full: full allele chosen by the pipeline.
• *_2field: allele collapsed to 2-field, useful when truth is low resolution.
• *_g_group: allele converted through SpecHLA hla_nom_g.txt.
• *_report: equals *_full by default; automatically downgraded to 2-field when a gene has high masked sequence fraction.
• *_fraction: modelled haplotype proportion for the reported R1/R2/D1/D2 call. In the standard 2+2 chimerism model, R haplotypes are chi_R / 2 each and D haplotypes are (1 - chi_R) / 2 each; EM/direct modes use the fitted gene-specific chi when available.
• *_read_fraction: allele-family read support fraction from EM read assignment (tf_counts.tsv). This is not forced to R1/R2 or D1/D2 being 1:1 and can differ between two alleles from the same person.
• *_read_count: EM-assigned effective read weight for the same 2-field allele family.
• *_copy_fraction_fit: fitted copy-level fraction for each R1/R2/D1/D2 slot. These four values sum to 1 when read support is available. The fit minimizes allele-family read-support error under x >= 0 and sum(x)=1, using the sample/gene chi as a weak regularizer when duplicated alleles make the copy split underdetermined. Values smaller than 1e-4 are written in scientific notation, so tiny values and exact boundary zeros are not displayed as fixed-width 0.000000.
• copy_fit_error, copy_identifiability, copy_chi_r, and allele_support_fraction_sum: diagnostics for the copy-fraction fit. boundary_zero means the constrained fit placed one slot at zero because it lacked independent support; it is not a filled missing value.
• mean_mask_fraction, report_level, warning: explain why a gene was reported at full vs. 2-field resolution.

The pipeline also writes a concise companion file, <SAMPLE>.final_calls.compact.tsv, with only the sample, gene, four reported alleles, four fitted copy fractions, per-allele read counts, and fit diagnostics. The original <SAMPLE>.final_calls.tsv remains the detailed result file.

For mixed donor/recipient samples, the primary side-agnostic report is now written as <SAMPLE>.copy_calls.tsv and <SAMPLE>.copy_calls.compact.tsv. These files list the four allele copies and their estimated proportions without making R/D assignment part of the main result. The long file carries both allele_read_count, the EM-assigned effective read count supporting each reported allele family, and copy_read_count, the same support apportioned across repeated copies of that allele according to the fitted copy fractions. The compact file carries these count vectors in the same order as copy_fractions. allele_read_count can be nonzero when a fitted duplicate copy fraction is zero, but copy_read_count will be zero for that row. The legacy R1/R2/D1/D2 slot is kept only as an annotation in the long file so old debugging workflows still have a bridge back to the assembly slots.

When DRB345_TYPING=1 (default), the pipeline also appends an HLA-DRB345 row. This is not a seventh ordinary locus: it is a DRB1-linked add-on for the DRB3/DRB4/DRB5 genes. The add-on extracts read pairs with competitive DB support for DRB3/4/5, EM-remaps them to a combined DRB345 allele set, and uses the final DRB1 haplotypes to decide whether each R1/R2/D1/D2 haplotype should carry DRB3, DRB4, DRB5, or no DRB345 gene. It does not change the classical or extended fixed-diploid gene calls. DRB345 DB-read extraction accepts bowtie2-style alignment scores, where the best score is often 0 and imperfect hits are negative. If the DRB1 row is high-mask / low-confidence, the add-on switches to an evidence-first mode: long locus-unique k-mers decide which DRB3/4/5 loci have credible support, then EM allele fractions are fit to the R/R/D/D dose model without hard DRB1 linkage. This lets DRB345 remain callable when DRB1 itself is unreliable.

The pipeline also writes <SAMPLE>.gene_abundance.tsv. Its fixed-diploid rows cover the six classical genes and the six default extended genes (HLA-E/F/G/H, MICA, and MICB), with global mixture, gene-local AF estimate, depth, residual, and local/global agreement fields. The global mixture remains restricted to the validated six classical genes. HLA-DRB3/4/5 are reported as three conditional copy-abundance rows: their low/high source copy counts come from the DRB1-linked four-haplotype result, and normal structural absence is reported explicitly. Non-PASS pooled mixture estimates propagate as low-confidence abundance rows rather than being presented as validated gene-level estimates.

The pipeline then writes <SAMPLE>.cnv_loh.tsv with exactly 15 rows. A joint four-haplotype MILP fits integer R1/R2/D1/D2 dosages in 0..3 against normalized gene depth and allele-group absolute dosage for the 12 fixed-diploid genes. DRB3/4/5 use their DRB1-linked structural state as the normal baseline and fit the three-locus EM read composition. DRB slot-level LOH evidence enters the objective only when every linked copy has a distinct allele group; repeated alleles are fitted at locus-total level because their slot dosage is not identifiable. It reports the exact best state, a no-good-cut second optimum, the baseline counterfactual, and their objective gaps. Total-copy changes are labeled CNV; a source-local 0/2 state at total copy four is labeled COPY_NEUTRAL_LOH. The state remains visible when an allele is shared across sources, but its confidence is ASSIGNMENT_AMBIGUOUS because the source carrying that dosage cannot be identified from the mixed sample alone. This diagnostic only reads final_calls.compact.tsv, gene_abundance.tsv, BAM, and DRB evidence; it does not change or refit the existing four-allele abundance predictions and does not rewrite HLA allele calls.

The per-gene FASTAs (hap{1..4}.fa) and raw calls.tsv are still kept under asm_v2/<SAMPLE>/<gene_lc>/<HLA-X>/ for inspection.

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4. Required inputs

Var	Meaning
FQ1, FQ2	paired short-read FASTQs (gz ok)
SAMPLE	sample id (used for output dirs)
RECIPIENT_MAJOR	0 = donor major (post-HSCT blood, default); 1 = recipient major (solid-organ / pre-transplant)

Optional environment / database overrides:

Var	Default	Meaning
SPECHLA	resources/spechla	bundled HLA resource root; override only for a custom database
PYBIN	first python on PATH	python binary
WHATSHAP	first whatshap on PATH	whatshap binary
FREEBAYES	first freebayes on PATH	freebayes binary; use 1.3.6 if newer builds abort
THREADS	8	threads for bowtie2, BWA, whatshap, EM remap, and samtools helper steps
SAMTOOLS_THREADS	$THREADS	threads for samtools view/sort/index/merge
WORK_DIR	parent of this repository	base for output dirs
OUT_ROOT	${WORK_DIR}/spechla_out	per-sample alignments + VCFs
ASM_ROOT	${WORK_DIR}/asm_v2	typing outputs
EXTRA_TYPING_GENES	HLA-E HLA-F HLA-G HLA-H MICA MICB	extended fixed-diploid loci; set to an explicit empty string to disable
EXTRA_TYPING_RESOURCE_ROOT	${WORK_DIR}/extra_typing_resources	temporary augmented references generated when EXTRA_TYPING_GENES is set
GENE_ABUNDANCE_OUTPUT	1	write <SAMPLE>.gene_abundance.tsv; set to 0 to disable
CNV_LOH_OUTPUT	1	write the joint integer-dosage <SAMPLE>.cnv_loh.tsv diagnostic; set to 0 to disable
POOLED_CHI_CONTIGS	core six reference contigs	contigs allowed to contribute to the global pooled mixture estimate
EXON_TYPING	1	also write exon-level fallback diagnostics (<SAMPLE>.exon_calls.tsv)
BOWTIE2_MODE	very-sensitive	bowtie2 preset for IMGT competitive mapping; use sensitive for faster exploratory runs
BOWTIE2_K	30	max alignments reported per read pair during IMGT competitive mapping
ASSEMBLE_ALIGNER	parasail	base-level scorer; mappy is faster but less exact
ASSEMBLE_PREFILTER_TOP	200	mappy prefilter size before parasail scoring; smaller is faster
EM_REFINE_PER_GENE_CHI	0	experimental; fixed pooled/global χ is the recommended default
EM_REFINE_RECIPIENT_MINOR_RESCUE	1	recover low-frequency recipient-only alleles when donor-major EM fitting collapses R/D to the donor-like pair
QUARTET_OPTIMIZATION_PROFILE	normalized_joint_v1	normalized_joint_v1 applies the frozen optimizers; shadow audits without rewriting calls; off disables the stage
REUSE_BINNING_ROOT	empty	seed deduped FASTQs, DB BAM, per-gene FASTQs, and header.sam from a prior run
REUSE_BINNING_CLEAN_DOWNSTREAM	0	remove downstream outputs after seeding cache when intentionally recomputing calls

The options above cover the recommended user-facing settings.

HLA-E/F/G/H and MICA/MICB are enabled by default and are included in the same final_calls.tsv and copy_calls.tsv outputs. To run only the validated six classical genes, explicitly disable the extended set:

EXTRA_TYPING_GENES="" \
bash polyphase_v2.sh

When the extended set is enabled, the driver automatically builds an augmented reference, gene BED, and per-gene BWA references under EXTRA_TYPING_RESOURCE_ROOT from the bundled IMGT-style FASTA. The global pooled χ estimate remains restricted to the classical six contigs, so enabling the extended set cannot change the established global estimator input. Extended gene calls and local abundance QC should still be treated as exploratory until validated with truth data for these loci.

Read-bin rescue is currently a validation-only diagnostic, not part of the default production pipeline. Run scripts/diagnostics/run_gendx_input_root_diagnostic.sh first to prove that strict gene binning is losing usable read evidence; only after a rerun shows accuracy gain should rescue be promoted into the main flow.

If indexes are missing after copying or replacing the resource directory, run:

bash build_resource_indexes.sh --resources "${SPECHLA:-resources/spechla}"

For exploratory reruns where speed matters more than final reporting, a useful starting point is:

THREADS=16 BOWTIE2_MODE=sensitive BOWTIE2_K=15 ASSEMBLE_PREFILTER_TOP=100 \
bash polyphase_v2.sh

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5. Tuning per sample

The pipeline auto-estimates the lower mixture component from the data. The pooled estimator is currently designed for mixture fractions in [0.10, 0.50]; lower fractions require separate validation. For boundary cases:

Situation	Override
χ_R < 0.03 (very deep chimerism)	FB_MIN_AF=0.005 FB_MIN_AC=2
χ_R > 0.50 (recipient majority)	RECIPIENT_MAJOR=1
Coverage < 50×	MASK_MIN_DEPTH=3
Coverage > 500×	MASK_MIN_DEPTH=10

For most samples, keep the defaults and only adjust the overrides above when the sample falls into one of those boundary cases.

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6. Outputs

asm_v2/<SAMPLE>/
<SAMPLE>.copy_calls.tsv ★ PRIMARY mixed-sample result (four sorted allele copies per gene)
<SAMPLE>.copy_calls.compact.tsv compact copy multiset/proportion/read-count result
<SAMPLE>.final_calls.tsv detailed R/D-slot aggregate result (one row per gene)
<SAMPLE>.final_calls.compact.tsv compact R/D-slot allele/proportion/read-count result
<SAMPLE>.gene_abundance.tsv 15-gene mixture/copy-abundance QC report
<SAMPLE>.cnv_loh.tsv joint four-haplotype integer CNV/LOH states
<SAMPLE>.exon_calls.tsv exon-level G group diagnostic for high-mask genes
<SAMPLE>.quartet_optimization.manifest.tsv baseline/proposal/gate/application audit
<gene_lc>/<HLA-X>/
calls.tsv per-gene final 4-hap call (R/D-tagged)
calls.baseline.tsv baseline before EM refinement (if overridden)
calls.quartet_optimization_input.tsv pre-optimization input (if rewritten)
hap{1..4}.fa per-haplotype masked FASTA
spechla_out/<SAMPLE>/ intermediate alignments + variants
<SAMPLE>.merge.bam, .freebayes.vcf.gz, .pooled_continuous.vcf.gz, ...
<SAMPLE>.chimerism.txt χ from AD-cluster estimator
<SAMPLE>.chi_pooled.txt χ from pooled-continuous (per gene)
read_bin_rescue_manifest.tsv rescue counts, retention gate, final status
class2_joint_rescue_manifest.tsv guarded class-II rescue audit trail
em_refine/<gene>.{calls,summary,iterative}.tsv
drb345/ DRB3/4/5 linked add-on typing outputs

• <SAMPLE>.final_calls.tsv columns: sample | gene | R1_full | R2_full | D1_full | D2_full | R1_2field | ... | R1_g_group | ... | R1_report | ... | R1_fraction | R2_fraction | D1_fraction | D2_fraction | R1_read_fraction | ... | R1_read_count | ... | R1_copy_fraction_fit | ... | copy_fit_error | copy_identifiability | copy_chi_r | allele_support_fraction_sum | source | mean_mask_fraction | report_level | warning.
• <SAMPLE>.final_calls.compact.tsv columns: sample | gene | R1_allele | R1_copy_fraction | R1_read_count | R2_allele | R2_copy_fraction | R2_read_count | D1_allele | D1_copy_fraction | D1_read_count | D2_allele | D2_copy_fraction | D2_read_count | copy_identifiability | copy_fit_error.
• <SAMPLE>.copy_calls.tsv columns: sample | gene | copy_id | copy_rank | allele | allele_2field | copy_fraction | allele_read_count | copy_read_count | proportion_source | legacy_slot | raw_copy_fraction | copy_identifiability | copy_fit_error.
• <SAMPLE>.copy_calls.compact.tsv columns: sample | gene | allele_multiset | allele_2field_multiset | copy_fractions | allele_read_counts | copy_read_counts | proportion_source | copy_identifiability | copy_fit_error.
• <SAMPLE>.gene_abundance.tsv columns: sample | gene | model | global_chi | global_chi_source | global_qc_status | global_ci95 | local_chi | n_af | median_dp | residual | delta_from_global | low_source_copies | high_source_copies | low_source_fraction | high_source_fraction | expected_gene_abundance | observed_low_fraction | observed_read_fraction | called_copies | status | reasons. Fixed-diploid rows use model=fixed_diploid; HLA-DRB3/4/5 use model=drb1_linked_conditional_copy. expected_gene_abundance is normalized to the abundance of a diploid gene, so a standard two-copy fixed locus is 1.0. DRB3/4/5 may be between 0.0 and 1.0 depending on source-specific presence and the mixture fraction.
• Abundance status values are PASS, LOW_CONFIDENCE, MODEL_MISMATCH, NOT_ENABLED, and NOT_RUN. A normal absent DRB3/4/5 locus is represented by status=PASS, expected_gene_abundance=0, and reasons=structural_absence. If pooled χ fails QC, the GT estimate can keep typing operational, but affected abundance rows remain LOW_CONFIDENCE.
• <SAMPLE>.cnv_loh.tsv includes normalized depth, four integer dosages, total copies, event, confidence, best/second/normal objectives, and event_support. ASSIGNMENT_AMBIGUOUS preserves a detected integer state while marking cross-source shared-allele attribution as non-identifiable.
• Per-gene calls.tsv columns: global_hap | assignment(R/D) | allele | hap_fraction | allele_read_fraction | allele_read_count | em_weight for EM-refined calls, or ... | hap_fraction | total_assembly_score for baseline assembly calls. DRB345 add-on calls are stored under asm_v2/<SAMPLE>/hla-drb345/HLA-DRB345/calls.tsv with an extra drb1_linked_locus column.

If truth is available, evaluate with:

python evaluate_calls.py \
--truth truth/truth_typing.tsv \
--calls asm_v2/mySample/mySample.final_calls.tsv

Evaluation reports only 2field and g_group accuracy. It intentionally does not score 3-field because many truth entries are 2-field or G group resolution. For G group scoring, truth alleles that cannot be uniquely mapped through hla_nom_g.txt remain at 2-field resolution instead of being treated as false mismatches.

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7. Re-running idempotently

SKIP_DONE=1 (default) skips steps whose output already exists. To force a re-run from a specific step, delete its output and re-invoke the driver:

rm spechla_out/mySample/mySample.freebayes.vcf.gz # re-do variant call
rm -r asm_v2/mySample # re-do typing
bash polyphase_v2.sh

For expensive real-data replays, reuse the dedup / competitive DB map / per-gene binning outputs and recompute only downstream steps:

REUSE_BINNING_ROOT=/path/to/previous/spechla_out \
REUSE_BINNING_CLEAN_DOWNSTREAM=1 \
SKIP_DONE=1 \
bash polyphase_v2.sh

When reporting accuracy, regenerate evaluation from the current final_calls.tsv; stale *.eval.txt files can describe an older call set.